1. Introduction. - 1. 1 Objective. - 1. 2 Background to Neural Networks. - 1. 3 Organization of book. - 2. Face Recognition. - 2. 1 Background. - 2. 2 Various methods. - 2. 3 Neural Net Approach. - 3. Implementation of Invariances. - 3. 1 Matching of similar triplets. - 3. 2 Software implementation. - 4. Simple Pattern Recognition. - 4. 1 Procedure. - 4. 2 Results. - 5. Facial Pattern Recognition. - 5. 1 Two-dimensional moment invariants. - 5. 2 Face Segmentation. - 5. 3 Isodensity regions. - 5. 4 Reducing sensitivity to lighting conditions. - 5. 5 Image encoding algorithm. - 5. 6 The use of gradient images. - 6. Network Training. - 6. 1 Training algorithms. - 6. 2 Modifications to training algorithms. - 6. 3 Training image data. - 6. 4 Results. - 7. Conclusions & Contributions 111. - 8. Future Work. - 8. 1 Simultaneous Training on all four Isodensity Images. - 8. 2 Higher-resolution coarse image size. - 8. 3 Automatic face recognition. - 8. 4 MIMO third-order networks. - 8. 5 Zernike and Complex moments. - 8. 6 Recognition of facial expressions (moods). - Index 119. Language: English